Lung cancer is the second most common cancer for both men and women in the United States, with an estimated 172,500 new cases projected to be diagnosed during 2005 (American Cancer Society statistics). It is the most common cause of cancer death for both sexes, with over 163,000 lung cancer related deaths expected in 2005. Lung cancer is also a major health problem in other areas of the world. In the European Union, approximately 135,000 new cases occur each year (Genesis Report, February 1995). Also, incidence is rapidly increasing in Central and Eastern Europe where men have the world's highest cigarette consumption rates (See, T. Reynolds, J. Natl. Cancer Inst. 87: 1348-1349 (1995)). Tobacco alone is responsible for over 90% of all cases of cancer of the lung, trachea, and bronchus (See, CPMCnet, Guide to Clinical Preventive Services). The International Agency for Research on Cancer of the World Health Organization estimated that in 2002, worldwide, there were 1,352,000 cases of lung cancer with 1,179,000 deaths due to the disease.
Early stage lung cancer can be detected by chest radiograph and the sputum cytological examination, however these procedures do not have sufficient accuracy to be routinely used as screening tests for asymptomatic individuals. The potential technical problems that can limit the sensitivity of chest radiograph include suboptimal technique, insufficient exposure, and positioning and cooperation of the patient (See, T. G. Tape, et al., Ann. Intern. Med. 104: 663-670 (1986)). Radiologists often disagree on interpretations of chest radiographs and over 40% of these are significant or potentially significant (See, P. G. Herman, et al., Chest 68: 278-282 (1975)). False-negative interpretations are the cause of most errors and inconclusive results require follow-up testing for clarification (See, T. G. Tape et al., supra).
Sputum cytology is less sensitive than chest radiography in detecting early lung cancer (See, The National Cancer Institute Cooperative Early Lung Cancer Detection Program, Am. Rev. Resp. Dis. 130: 565-567 (1984)). Factors affecting the ability of sputum cytology to diagnose lung cancer include the ability of the patient to produce sufficient sputum, the size of the tumor, the proximity of the tumor to major airways, the histologic type of the tumor, and the experience and training of the cytopathologist (See, R. J. Ginsberg et al. In: Cancer: Principles and Practice of Oncology, Fourth Edition, pp. 673-723, Philadelphia, Pa.: J/B. Lippincott Co. (1993)).
Most new lung cancers will be detected when the disease has spread beyond the lung. In the United States only 16% of new non-small cell lung cancers are detected at a localized stage when 5-year survival is highest at 49.7%. In contrast, 68% of new cases are detected when the disease has already spread locally or metastasized to distant sites that have 5-year survival rates of 18.5% and 1.8%, respectively. Similarly, 80% of newly detected small-cell lung cancers are discovered with local invasion or distant metastasis which have 5 year survival rates of 9.5% and 1.7%, respectively (See, Stat Bite, J. Natl. Cancer Inst. 87:1662 (1995)). These statistics show that current procedures are failing to detect lung cancer at an early, treatable stage of the disease and that improved methods of detection and treatment are needed to reduce mortality.
The most frequently used methods for monitoring lung cancer patients after primary therapy are clinic visit, chest X-ray, complete blood count, liver function testing and chest computed tomography (CT). Detecting recurrence by regular monitoring, however, does not greatly affect the mode of treatment and the overall survival time leading to the conclusion that current monitoring methods are not cost effective (See, K. S. Naunheim et al., Ann. Thorac. Surg. 60:1612-1616 (1995); G. L. Walsh et al., Ann. Thorac. Surg. 60: 1563-1572 (1995)).
More recently, there has been a re-examination of the use of computed tomography (CT) to screen asymptomatic persons who are at high risk for lung cancer. C. I. Henschke et al., (Clin. Imaging 28:317-321 (2004)) reported two studies that indicated that CT scanning can detect asymptomatic lung cancer without generating too many false positives. J. Gohagan et al., (Chest 126:114-121 (2004)) evaluated a trial protocol for a randomized study comparing chest X-ray with low dose spiral CT and concluded that a large randomized clinical trial to screen for lung cancer was feasible. However, even if implemented in clinical practice, the cost of CT screening would be high and the number of false positives leading to additional testing would also be high. A low cost blood test with good specificity would complement CT for the early detection of cancer. Another strategy for improving the utility of CT involves the use of a high sensitivity blood test for early stage lung cancer. Such a test could be offered to patients as an alternative to CT or X-ray. If the test were positive, the patient would be imaged; if the test were negative, the patient would not be scanned, but could be retested in the future. Whether a blood test offers high sensitivity or high specificity or, ideally, both, such a test would find utility in the current protocols used to detect early stage lung cancer.
Additionally, there has been a recent re-examination of tumor markers and their usefulness when combined into panels to identify individuals who are at risk for lung cancer. However, the lack of sensitivity that was characteristic of individual markers still prevents panels of tumor markers from being useful for early detection of lung cancer. The tumor antigens that have been found by classical biochemical methods, including alpha Fetoprotein (AFP), CA19-9, CA125, Carcinoembryonic Antigen (CEA), Cytokeratin 8, Cytokeratin 18, Cytokeratin 19 fragments (CYFRA 21-1), Neuron-Specific Enolase (NSE), pro-Grastrin-Releasing Peptide (proGRP), and Squamous Cell Carcinoma Antigen (SCC). These markers have been found to be useful in staging, classifying, predicting outcomes for, and monitoring of lung cancer patients after their diagnosis has been made; however, these markers have not been found to be useful, either alone or in panels, for the early detection of the disease (See, S. Ando, et al., Anticancer Res. 21: 3085-3092 (2001); U.S. Preventive Services Task Force, Annals of Internal Medicine 140:738-739 (2004)). In contrast, a panel of known immunoassay markers, specifically, CEA, CYFRA 21-1, SCC, NSE, and ProGRP, are known to be useful in making a histological diagnosis of lung cancer in those circumstances when obtaining a biopsy sample is difficult (See, C. Gruber et al., Tumor Biology 27 (Supplement 1): 71 (2006) and P. Stieber et al., Tumor Biology, 27 (Supplement 2):S5-4 (2006)).
Attempts have been made to discover improved tumor markers for lung cancer by first identifying differentially expressed cellular components in lung tumor tissue compared to normal lung tissue. Two-dimensional polyacrylamide gel electrophoresis has been used to characterize quantitative and qualitative differences in polypeptide composition (See, T. Hirano et al., Br. J. Cancer 72:840-848 (1995); A. T. Endler et al., J. Clin. Chem Clin. Biochem. 24:981-992 (1986)). The sensitivity of this technique, however, is limited by the degree of protein resolution of the two electrophoretic steps and by the detection step that depends on staining protein in gels. Also, polypeptide instability will generate artifacts in the two-dimensional pattern.
Attempts have also been made to identify biomarkers and their use in aiding in the diagnosis of lung cancer, such as those described in International Publication No. WO 2005/098445 A2. The biomarkers discussed in WO 2005/098445 were identified using surface-enhanced laser desorption/ionization mass spectrometry (SELDI). Various markers, kits, methods and a decision tree analytical method are disclosed. However, these markers, kits and methods have not been adopted for use in routine practice as these markers and methods have not been duplicated in any laboratory.
The human immune system has long been known to be involved in the development and control of cancer (See, K. de Visser, et al., Nature Reviews Cancer, 6: 24-37 (2006)). Therefore, it is not surprising that proteins representing both the innate and the adaptive immune response have been explored as tumor markers for lung cancer.
Acute phase proteins, members of the innate immune family of proteins, including serum amyloid A (SAA), serum amyloid P (SAP), and C-reactive protein (CRP), alpha-1-antichymotrypsin (alpha-1-ACT), alpha-1-antitrypsin (alpha-1-AT), alpha-2-macroglobulin (alpha-2-M), ceruloplasmin (Cp), haptoglobin (Hp), and transferrin (Tf) have been evaluated as biomarkers in early, resectable, lung cancer (See, M. Kasprzyk, et al., Przegl. Lek., 63: 936-940 (2006)). Fibrinogen and CRP have been studied as biomarkers for resectable lung cancer (See, J. Jones, et al., Lung Cancer, 53: 97-101 (2006)). Apolipoprotein CIII (apoCIII) has been not been reported to be a biomarker for lung cancer, but it has been reported to be associated with pancreatic cancer (See, J. Chen, et al., J. Chromatogr. A, (2007), doi: 10.1016/j.chroma.2007.03.096). The association of acute phase proteins with lung cancer has been known for more than 2 decades (See, P. Weinstein, et al., Scand. J. Immunol. 19: 193-198 (1984)); however, no acute phase protein is routinely used in the diagnosis of early stage lung cancer.
There are proteins which are not usually thought to be acute phase proteins, but which are elevated in response to a stress on the subject. Such proteins can be termed host response proteins, a broader category than innate or adaptive immune proteins. One such protein is thymosin beta-4 (TP4), a 44 amino acid peptide which is involved in wound healing. Expression of thymosin beta-4 in tumor tissue is thought to predict a more aggressive and metastatic phenotype for the tumor. Early stage lung cancer patients who express thymosin beta-4 mRNA at high levels have worse survival than patients with lower expression (See, C. Muller-Tidow, et al., Lung Cancer 45: S145-150 (2004)).
Autoantibodies, immunoglobulins which react with a patients own proteins (termed autoantigens), comprise the proteins which implement the actions of the adaptive immune system. Scientific publications on the presence of autoantibodies in lung cancer patients date back 40 years (See, G. Levine, et al., J. Lab. Clin. Med. 69: 749-757 (1967)). Occasionally, particularly in small cell lung cancer, autoantibodies against nervous system components result in the patient exhibiting neurological symptoms characterized as a paraneoplastic syndrome (See, U. Seneviratne, et al., Postgrad. Med. J. 75: 516-520 (1999)). Although dramatic, very few patients exhibit a paraneoplastic syndrome, so neither the syndrome nor autoantibodies against neurological cells or proteins are diagnostically useful for the population at large. The early autoantibody literature has numerous references to circulating anti-p53 antibodies. P53 is a tumor supressor protein which is inactivated by mutation in many cancers. Although patient anti-p53 antibodies react with both native and mutated p53, it is thought that the longer tissue half-life of mutated p53 results in the appearance of this autoantibody in about 30% of lung cancer patients (See, R. Lubin, et al., Nat. Med. 1: 701-702 (1995)). There are reports of intracellular proteins, involved in the regulation of cell machinery, which give rise to autoantibodies in cancer. Antibodies to human heat shock protein 40 (Hsp40) have been reported to be found in the serum of lung cancer patients (See, M. Oka, et al., Jpn. J. Cancer Res. 92: 316-320 (2001)). This protein is also known as DnaJB1 or hDJ1. Although many proteins have been described which become autoantigens, giving rise to circulating autoantibodies in lung cancer, given the million or more proteins thought to exist in a human subject, there remain many more proteins, both known and unknown, which may prove to be cause diagnostically useful autoantibodies in patients with lung cancer and other chronic diseases.
If multiple autoantibodies are used to classify patients or make a diagnosis, a data analysis protocol is required. J. Koziol, et al., (Clin. Cancer Res. 9:5120-5126 (2003)) used recursive partitioning to select autoantibodies for optimal diagnosis of various tumors. They used seven tumor associated antigens: c-myc, cyclin B1, IMP2, Koc, p53, p62, and survivin and achieved good results for a small group (56) of lung cancer patients.
Systematic approaches to find diagnostically useful autoantibodies include the use of protein arrays to screen patient and disease-free sera for reactive autoantibodies. Arrays have been constructed from tumor cell lysates (See, J. Qiu, et al., J. Proteome Res. 3:261-267 (2004)) and used to search for novel autoantigens which give rise to diagnostically useful autoantibody signatures in patient sera. Arrays can also be constructed from recombinantly expressed proteins (See, D. Mattoon, et al., Expert. Rev. Proteomics 2: 879-889 (2005)). Affinity chromatography methodologies have been described which may prove useful to find diagnostic autoantibodies (J. Sep. Sci. 30:352-358 (2007)). To date none of these approaches have yielded novel autoantibodies useful for the early detection of lung cancer.
Another systematic approach to discovering diagnostically useful autoantibodies is the so-called SEREX method. SEREX stands for Serological Analysis of Recombinant cDNA Expression Libraries and has been used to discover a novel testicular antigen which is aberrantly expressed in a variety of cancers (See, Y. Chen, et al., Proc. Natl. Acad. Sci. U.S.A. 94: 1914-1918 (1997)). NY-ESO-1 is a protein of about 18 kD and has been extensively studied as a tumor autoantibody. Approximately 20% of non-small cell lung cancer patients have circulating antibodies against the protein as measured by an ELISA (See, O. Tureci, et al., Cancer Lett. 236: 64-71 (2006)).
Attempts have also been made to discover an immune response specific for lung cancer by surveying peptide libraries expressed in yeast or bacteria with sera from diseased and non-diseased individuals. Publications from the laboratory of Hirschowitz (See, L. Zhong et al., Chest 125:105-106 (2004), L. Zhong et al., Am. J. Respir. Crit. Care Med. 15:1308-1314 (2005)) have described the use of phage libraries to find proteins which are autoantigens to patients with lung cancer. The authors have reported on the successful identification of both symptomatic and asymptomatic lung cancer patients in controlled studies. However, the number of cases and controls are limited (<200 total subjects) and the method needs to be validated on a much larger population.
Currently, the identification of individuals at risk for lung cancer is based largely on the smoking history of the individual. Other environmental exposures such as asbestos, particulates, etc., can increase the risk of developing lung cancer as well. These known risk factors have been combined in one or more algorithms and are accessible to clinicians and the public for assessing the risk of individuals for lung cancer (See, P. B. Bach et al., J. Natl. Cancer Inst. 95:470-478 (2003)). Unfortunately, this algorithm is neither sensitive nor specific enough to be useful for the detection of early stage lung cancer. Indeed, based on the cited algorithm, an individual with a significant smoking history will have a relative risk of 1/500 to 1/100 for developing lung cancer. This means that even using the method of Bach et al. as many as 499 out of 500 CT scans will not lead to the discovery of a case of lung cancer.
Thereupon, there remains a need in the art for methods and markers useful for detecting lung cancer that are fast, convenient and cost-effective to perform. It would also be advantageous to provide specific methods and certain combinations of markers that could be used to determine whether a patient is at risk of developing lung cancer or has lung cancer. Such methods would include a method for testing a sample for one or more markers indicative of lung cancer and detecting such markers. Such methods can include improved methods for analyzing mass spectra of a biological sample for markers or assaying a sample and then detecting markers as a risk of developing lung cancer or as indication of lung cancer.